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We consider the numerical taxonomy problem of fitting a positive distance function ${D:{S\choose 2}\rightarrow \mathbb R_{>0}}$ by a tree metric. We want a tree $T$ with positive edge weights and including $S$ among the vertices so that…

Data Structures and Algorithms · Computer Science 2022-03-14 Vincent Cohen-Addad , Debarati Das , Evangelos Kipouridis , Nikos Parotsidis , Mikkel Thorup

In this paper we develop algorithms for approximating matrix multiplication with respect to the spectral norm. Let A\in{\RR^{n\times m}} and B\in\RR^{n \times p} be two matrices and \eps>0. We approximate the product A^\top B using two…

Data Structures and Algorithms · Computer Science 2010-10-28 Avner Magen , Anastasios Zouzias

For any real numbers $B \ge 1$ and $\delta \in (0, 1)$ and function $f: [0, B] \rightarrow \mathbb{R}$, let $d_{B; \delta} (f) \in \mathbb{Z}_{> 0}$ denote the minimum degree of a polynomial $p(x)$ satisfying $\sup_{x \in [0, B]} \big| p(x)…

Computational Complexity · Computer Science 2022-05-13 Amol Aggarwal , Josh Alman

The classical work of (Arora et al., 1999) provides a scheme that gives, for any $\epsilon>0$, a polynomial time $1-\epsilon$ approximation algorithm for dense instances of a family of $\mathcal{NP}$-hard problems, such as Max-CUT and…

Data Structures and Algorithms · Computer Science 2024-05-24 Evripidis Bampis , Bruno Escoffier , Michalis Xefteris

Many problems are NP-hard and, unless P = NP, do not admit polynomial-time exact algorithms. The fastest known exact algorithms exactly usually take time exponential in the input size. Much research effort has gone into obtaining faster…

Data Structures and Algorithms · Computer Science 2025-01-27 Stefan Kratsch , Pascal Kunz

We consider the Low Rank Approximation problem, where the input consists of a matrix $A \in \mathbb{R}^{n_R \times n_C}$ and an integer $k$, and the goal is to find a matrix $B$ of rank at most $k$ that minimizes $\| A - B \|_0$, which is…

Data Structures and Algorithms · Computer Science 2023-11-03 Vincent Cohen-Addad , Chenglin Fan , Suprovat Ghoshal , Euiwoong Lee , Arnaud de Mesmay , Alantha Newman , Tony Chang Wang

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

We give a polynomial time algorithm to decode multivariate polynomial codes of degree $d$ up to half their minimum distance, when the evaluation points are an arbitrary product set $S^m$, for every $d < |S|$. Previously known algorithms can…

Computational Complexity · Computer Science 2015-11-25 John Kim , Swastik Kopparty

We give an algorithm for properly learning Poisson binomial distributions. A Poisson binomial distribution (PBD) of order $n$ is the discrete probability distribution of the sum of $n$ mutually independent Bernoulli random variables. Given…

Data Structures and Algorithms · Computer Science 2015-11-13 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

We show that, assuming the (deterministic) Exponential Time Hypothesis, distinguishing between a graph with an induced $k$-clique and a graph in which all k-subgraphs have density at most $1-\epsilon$, requires $n^{\tilde \Omega(log n)}$…

Computational Complexity · Computer Science 2015-05-01 Mark Braverman , Young Kun Ko , Aviad Rubinstein , Omri Weinstein

Traditionally, robust statistics has focused on designing estimators tolerant to a minority of contaminated data. Robust list-decodable learning focuses on the more challenging regime where only a minority $\frac 1 k$ fraction of the…

Data Structures and Algorithms · Computer Science 2020-11-20 Ilias Diakonikolas , Daniel M. Kane , Daniel Kongsgaard , Jerry Li , Kevin Tian

The study of Markov processes and broadcasting on trees has deep connections to a variety of areas including statistical physics, graphical models, phylogenetic reconstruction, Markov Chain Monte Carlo, and community detection in random…

Probability · Mathematics 2022-10-26 Frederic Koehler , Elchanan Mossel

The determinantal complexity of a polynomial $P \in \mathbb{F}[x_1, \ldots, x_n]$ over a field $\mathbb{F}$ is the dimension of the smallest matrix $M$ whose entries are affine functions in $\mathbb{F}[x_1, \ldots, x_n]$ such that $P =…

Computational Complexity · Computer Science 2021-12-03 Mrinal Kumar , Ben Lee Volk

Polynomial-time deterministic approximation of volumes of polytopes, up to an approximation factor that grows at most sub-exponentially with the dimension, remains an open problem. Recent work on this question has focused on identifying…

Combinatorics · Mathematics 2026-03-16 Hariharan Narayanan , Piyush Srivastava

For a graph $G$, let $Z(G,\lambda)$ be the partition function of the monomer-dimer system defined by $\sum_k m_k(G)\lambda^k$, where $m_k(G)$ is the number of matchings of size $k$ in $G$. We consider graphs of bounded degree and develop a…

Data Structures and Algorithms · Computer Science 2013-09-05 Marc Lelarge , Hang Zhou

We give a polynomial-time approximation algorithm for the (not necessarily metric) $k$-Median problem. The algorithm is an $\alpha$-size-approximation algorithm for $\alpha < 1 + 2 \ln(n/k)$. That is, it guarantees a solution having size at…

Data Structures and Algorithms · Computer Science 2025-11-18 Neal E. Young

We examine the possibility of approximating Maximum Vertex-Disjoint Shortest Paths. In this problem, the input is an edge-weighted (directed or undirected) $n$-vertex graph $G$ along with $k$ terminal pairs…

Data Structures and Algorithms · Computer Science 2025-04-23 Matthias Bentert , Fedor V. Fomin , Petr A. Golovach

For a metric graph $G=(V,E)$ and $R\subset V$, the internal Steiner minimum tree problem asks for a minimum weight Steiner tree spanning $R$ such that every vertex in $R$ is not a leaf. This note shows a simple polynomial-time…

Data Structures and Algorithms · Computer Science 2013-07-18 Bang Ye Wu

Deep learning algorithms have been successfully applied to numerically solve linear Kolmogorov partial differential equations~(PDEs). A recent research shows that if the initial functions are bounded, the empirical risk minimization (ERM)…

Numerical Analysis · Mathematics 2024-06-25 Jichang Xiao , Xiaoqun Wang

We study the low-degree hardness of broadcasting on trees. Broadcasting on trees has been extensively studied in statistical physics, in computational biology in relation to phylogenetic reconstruction and in statistics and computer science…

Probability · Mathematics 2024-02-22 Han Huang , Elchanan Mossel
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